Objective:
1) Identify putative gene-by-environment (GxE) interaction SNPs by merging genes with known eQTLs from several published studies, with genes showing consistent altered expression across published human and rodent experiments centered on specific environmental challenges, e.g. high-fat diet, caloric restriction, exercise or alcohol exposure.
2) Identify genes with a strong likelihood to exhibit GxE interactions by building separate gene/protein networks first seeded by genes harboring SNPs that direct allele-specific interactions either to important MetS phenotypes or Environmental Factors (EFs): total dietary fat plus five other types of dietary fat, total carbohydrate or protein, exercise, or alcohol or smoking use, and then extended with protein-protein interaction data.
3) Test for actual and significant GxE interactions in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) and Framingham Heart Study (FHS) populations using the genes and SNPs prioritized by Aims 1 and 2 along with the environmental term elucidated in those two Aims.

Approach:
Use bioinformatics approaches to identify genes with a strong likelihood of responding to dietary components, physical activity, or alcohol use. Use an integrated genomics methodology to identify putative GxE variants. This method is based on the merging of large, genome-wide datasets with subsequent filtering to identify the elements (e.g. genes) with the most or best attributes.